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Adafruit
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AI
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Projects relevant or used for my Master's thesis.2 repositories
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Starred repositories
A modern and transparent way to use Windows VST2, VST3 and CLAP plugins on Linux
isd (interactive systemd) – a better way to work with systemd units
An AI-powered research assistant that performs iterative, deep research on any topic by combining search engines, web scraping, and large language models. The goal of this repo is to provide the si…
🪄 Create rich visualizations with AI
Anime Girls Holding Programming Books
Automate gate/garage door opening via 433.92MHz emitter with Raspberry Pi, Home Assistant and Homekit.
The “Quite OK Audio Format” for fast, lossy audio compression
📚 A curated list of papers for Software Engineers
Python tool for converting files and office documents to Markdown.
Hardened Fedora Atomic and Fedora CoreOS images
✨ The Next Gen Airtable Alternative: No-Code Postgres
BlueBuild standard modules used for building your Atomic Images
An extremely fast Python package and project manager, written in Rust.
Harden Windows Safely, Securely using Official Supported Microsoft methods and proper explanation | Always up-to-date and works with the latest build of Windows | Provides tools and Guides for Pers…
The comprehensive .NET Developer Roadmap for 2025 by seniority level.
Meta Lingua: a lean, efficient, and easy-to-hack codebase to research LLMs.
DNA Transcription Factor Binding Prediction (Self-learning Project)
A modern GTK Theme Manager for GNOME with GTK 4.0 support and some cool features.
📺 Discover the latest machine learning / AI courses on YouTube.
Inverse RL algorithms (APP, MaxEnt, GAIL, VAIL)
Chai-1, SOTA model for biomolecular structure prediction
OpenRecall is a fully open-source, privacy-first alternative to proprietary solutions like Microsoft's Windows Recall. With OpenRecall, you can easily access your digital history, enhancing your me…
This is an open surce alternative at microsof recall and at OpenRecall (sorry... but OpenRecall isn't working on my waylnad KDE Arhc linux)
bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent